An improved reversible image watermarking algorithm based on difference expansion

Zhang, Zhengwei; Wu, Lifa; Yan, Yunyang; Xiao, Shaozhang; Sun, He

doi:10.1177/1550147716686577

Cited by 13 publications

(5 citation statements)

References 25 publications

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“…The PSNR is another measurement to find the effect of adding a watermark to an object, embedding the watermark, and modifying the object shape by changing the vertices values. The PSNR can be calculated using equation ( 4) [19,20].…”

Section: Resultsmentioning

confidence: 99%

Watermarking of a 3D Model based on Wavelet Transform

Laftah

2021

eijs

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In the last decade, 3D models gained interest in many applications, such as games, the medical field, and manufacture. It is necessary to protect these models from unauthorized copying, distribution, and editing. Digital watermarking is the best way to solve this problem. This paper introduces a robust watermarking method by embedding the watermark in the low-frequency domain, then selecting the coarsest level for embedding the watermark based on the strength factor. The invisibility of the watermark for the proposed algorithm is tested by using different measurements, such as HD and PSNR. The robustness was tested by using different types of attacks; the correlation coefficient was applied for the evaluation of the extracted watermark. From the results, it is clear that the proposed algorithm achieved good invisibility and robustness against the geometrical attack and the added noise.

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Section: Resultsmentioning

confidence: 99%

Watermarking of a 3D Model based on Wavelet Transform

Laftah

2021

eijs

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“…To determine the watermarked model imperceptibility, Mean Square Error (MSE) metrics are shown in Eq. ( 4) [24][25][26].…”

Section: Extraction Algorithmmentioning

confidence: 99%

Data Hiding in 3D Model Based on Surface Properties

Ali

2023

Iraqi Journal of Science

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Data hiding strategies have recently gained popularity in different fields; Digital watermark technology was developed for hiding copyright information in the image visually or invisibly. Today, 3D model technology has the potential to alter the field because it allows for the production of sophisticated structures and forms that were previously impossible to achieve. In this paper, a new watermarking method for the 3D model is presented. The proposed method is based on the geometrical and topology properties of the 3D model surface to increase the security. The geometrical properties are based on computing the mean curvature for a surface and topology based on the number of edges around each vertex, the vertices that have negative mean curvature and an odd number of edges around the vertex are selected for embedding. Selecting the vertex with negative mean curvature value means the vertex located in the deep region of the surface, so it not noticeable change to human eyes. To evaluate the performance of the proposed algorithm, the PSNR, and CF are used as a measurement to evaluate the visibility and robustness of the 3D watermarked model. The experimental results have shown the proposed algorithm has good imperceptibility where the PSNR reach up to 44.41 and robustness against attack where the CF is one in many cases.

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“…In order to improve the security of the original watermark information in practical applications, the watermark information is preprocessed by scrambling transformation before the construction of zero-watermark image. In this paper, we choose the Arnold transform for watermark scrambling [32,33]. The calculate of the Arnold transform can be mathematically expressed as the following Equation…”

Section: The Scrambled Of Original Watermark Informationmentioning

confidence: 99%

A zero-watermarking algorithm for vector geographic data based on feature invariants

Wang

Zhang

et al. 2022

Earth Sci Inform

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Most researches on zero-watermarking algorithms for vector geographic data focus on improving the robustness against geometrical attacks, compression attacks and object attacks. However, there are few zero-watermarking algorithms against projection transformation. We proposed a zerowatermarking algorithm for vector geographic data based on feature invariants. After any projection transformation of vector geographic data, the number of vertices and relative storage order of objects does not change. Therefore, the number of vertices and relative storage order of objects can be considered as the feature invariants. Firstly, according to relative storage order of objects, the watermark bit is determined by comparing the number of vertices between any two objects. Secondly, the watermark index is calculated by the number of vertices of two objects. Then, a feature matrix is constructed combining the watermark bit and the watermark index. Finally, the XOR operation is performed between the feature matrix and the scrambled watermark image to generate the zerowatermark image. The experiments show that the watermark can be detected from the vector geographic data after any projection transformation. And this algorithm can effectively against geometrical attacks, object attacks and precision reduction attacks, showing superior performance compared with previous algorithms.

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An improved reversible image watermarking algorithm based on difference expansion

Cited by 13 publications

References 25 publications

Watermarking of a 3D Model based on Wavelet Transform

Watermarking of a 3D Model based on Wavelet Transform

Data Hiding in 3D Model Based on Surface Properties

A zero-watermarking algorithm for vector geographic data based on feature invariants

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